There are two types of data used in this paper, the first is a proprietary historical sugar (SB) futures data set and the second is public historical stock data set for a variety of stocks including AMZN, FB, MSFT and more as described in and retrieved from [1]}. These two asset classes are seemingly unrelated, but it can be shown that most financial assets share some universal features which work well with the proposed models involving Hawkes processes. The set of SB futures data consists of every individual update to the top ten levels of the limit order books price and volume levels over a several month period starting in January 2021. Every row in this data corresponds to an LOB update, that is every time one feature changes another row of data is generated. As an effect there can be many stagnant periods where prices won't update, but the volume available at a certain level of depth will. This is a side effect of the ability to cancel active orders or submit new orders to the limit order book on a free flowing basis. Similarly, the public stock data also contains ten levels of limit order book price and volume data over a one month window in November 2014 (18 to 20 days per stock). This data is updated after every market order hence, is less abundant than the futures data while still tracking the evolution of the mid-price.
<FIGURE>